ArticlePLoS genetics2015
Evolutionary signatures amongst disease genes permit novel methods for gene prioritization and construction of informative gene-based networks.
Article in PLoS genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed.
- Evolutionary Rate Covariation Across Malaria Parasite Species Enables Inference of Protein Interactions.Genome biology and evolution · 2026Article
- Multi-organ single-cell analysis of preferential expression of CAKUT genes.BMC nephrology · 2026Article
- Correlated Evolutionary Rates Reveal Novel Components and Cross-Compartment Connectivity in Plant Proteostasis Systems.Genome biology and evolution · 2026Article
- Evolutionary rate covariation across malaria parasite species enables inference of protein interactions.bioRxiv : the preprint server for biology · 2026Article
- ERC2.0 evolutionary rate covariation update improves inference of functional interactions across large phylogenies.Genome research · 2025Article
- ERCnet: Phylogenomic Prediction of Interaction Networks in the Presence of Gene Duplication.Molecular biology and evolution · 2025Article
- ERC 2.0 - evolutionary rate covariation update improves inference of functional interactions across large phylogenies.bioRxiv : the preprint server for biology · 2025Article
- Evolutionary rate covariation is pervasive between glycosylation pathways and points to potential disease modifiers.PLoS genetics · 2024Article
- Analysis of Evolutionary Conservation, Expression Level, and Genetic Association at a Genome-wide Scale Reveals Heterogeneity Across Polygenic Phenotypes.Molecular biology and evolution · 2024Article
- Standigm ASK™: knowledge graph and artificial intelligence platform applied to target discovery in idiopathic pulmonary fibrosis.Briefings in bioinformatics · 2024Article
- Speos: an ensemble graph representation learning framework to predict core gene candidates for complex diseases.Nature communications · 2023Article
- MAIA, Fc receptor-like 3, supersedes JUNO as IZUMO1 receptor during human fertilization.Science advances · 2022Article
- Multiple 9-1-1 complexes promote homolog synapsis, DSB repair, and ATR signaling during mammalian meiosis.eLife · 2022Article
- Evolutionary rate covariation identifies SLC30A9 (ZnT9) as a mitochondrial zinc transporter.The Biochemical journal · 2021Article
- Novel ACE2 protein interactions relevant to COVID-19 predicted by evolutionary rate correlations.PeerJ · 2021Article
- AeLife · 2020Article
- MCM8IP activates the MCM8-9 helicase to promote DNA synthesis and homologous recombination upon DNA damage.Nature communications · 2020Article
- Molecular evolution of the meiotic recombination pathway in mammals.Evolution; international journal of organic evolution · 2019Article
- Evolution-based screening enables genome-wide prioritization and discovery of DNA repair genes.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Evolutionary rate covariation analysis of E-cadherin identifies Raskol as a regulator of cell adhesion and actin dynamics in Drosophila.PLoS genetics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Genes involved in the same function tend to have similar evolutionary histories, in that their rates of evolution covary over time. This coevolutionary signature, termed Evolutionary Rate Covariation (ERC), is calculated using only gene sequences from a set of closely related species and has demonstrated potential as a computational tool for inferring functional relationships between genes. To further define applications of ERC, we first established that roughly 55% of genetic diseases posses an ERC signature between their contributing genes. At a false discovery rate of 5% we report 40 such diseases including cancers, developmental disorders and mitochondrial diseases. Given these coevolutionary signatures between disease genes, we then assessed ERC's ability to prioritize known disease genes out of a list of unrelated candidates. We found that in the presence of an ERC signature, the true disease gene is effectively prioritized to the top 6% of candidates on average. We then apply this strategy to a melanoma-associated region on chromosome 1 and identify MCL1 as a potential causative gene. Furthermore, to gain global insight into disease mechanisms, we used ERC to predict molecular connections between 310 nominally distinct diseases. The resulting "disease map" network associates several diseases with related pathogenic mechanisms and unveils many novel relationships between clinically distinct diseases, such as between Hirschsprung's disease and melanoma. Taken together, these results demonstrate the utility of molecular evolution as a gene discovery platform and show that evolutionary signatures can be used to build informative gene-based networks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.